Publication Date:
2022-06-20
Description:
Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.
Description:
This work has been partially funded by the European Commission funded projects MyOcean, MyOcean2 and COMBINE; by the GEMINA project-funded bythe Italian Ministry for Environment; by the
NERC-funded VALOR project; by the NERC-funded NCEO program; by the Research Program on Climate Change adaptation of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government; by
the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101); by NASA’s Modeling Analysis and Prediction Program under WBS 802678.02.17.01.25 and
by the NASA Physical Oceanography Program;
by the NOAA's Climate Observation Division (COD); by the LEFE/GMMC French national program.
Description:
Published
Description:
s80-s97
Description:
4A. Clima e Oceani
Description:
JCR Journal
Description:
open
Keywords:
Global ocean–sea-ice modelling
;
Ocean model comparisons
;
DATA ASSIMILATION SCHEME
;
multi-analysis ensemble
;
Ocean climate
;
03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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